# World Bank Development Goals - Free SDG Tracking API (`ntriqpro/world-bank-development-goals`) Actor Free API for UN Sustainable Development Goals (SDG) tracking. No subscription. Track progress by country for poverty, health, education, development metrics. Government data, pay-per-use. - **URL**: https://apify.com/ntriqpro/world-bank-development-goals.md - **Developed by:** [daehwan kim](https://apify.com/ntriqpro) (community) - **Categories:** AI, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $100.00 / 1,000 charged when a workforce and labor intelligence ans This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Workforce & Labor Intelligence - BLS/Census Data Replaces Lightcast/EMSI ($10K-$20K/yr) using free BLS, Census QWI, and O*NET APIs. 5 modes: occupation analysis, labor market, wage trends, industry workforce, and skills demand. SOC-level wage data, hiring rates, and employment projections at $0 per query. ### Features - Analyze any occupation with SOC-level wage data, employment counts, and outlook projections from BLS - Retrieve regional labor market statistics using Census Quarterly Workforce Indicators (QWI) - Track wage trends over time with BLS Occupational Employment and Wage Statistics (OEWS) - Profile industry workforce composition including hiring rates and separation trends by NAICS code - Identify skills demand and in-demand competencies using O*NET occupation data ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `mode` | string | Analysis mode: `occupation_analysis`, `labor_market`, `wage_trends`, `industry_workforce`, `skills_demand` | `occupation_analysis` | | `occupation` | string | Occupation name to analyze (e.g., 'software developer', 'registered nurse', 'data scientist') | — | | `socCode` | string | Standard Occupational Classification (SOC) code (e.g., '15-1252' for Software Developers) | — | | `state` | string | Two-letter US state abbreviation for regional labor market data (e.g., 'CA', 'TX', 'NY') | — | | `industryCode` | string | 2-6 digit NAICS industry code (e.g., '54' for Professional Services, '62' for Healthcare) | — | | `years` | integer | Number of years of historical wage trend data to retrieve (1-10) | `5` | ### Output The actor returns structured JSON data with wage statistics, employment counts, growth projections, skills inventories, and regional labor market snapshots. ### Pricing This actor uses pay-per-event pricing at $0.05 per successful analysis. ### Usage 1. Set your input parameters 2. Run the actor 3. Get results from the dataset ### API Integration ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('ntriqpro/workforce-labor-intelligence').call({ mode: 'occupation_analysis', occupation: 'software developer', state: 'CA', }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); ```` # Actor input Schema ## `mode` (type: `string`): Select the type of workforce and labor market analysis to perform ## `occupation` (type: `string`): Occupation name to analyze (e.g., 'software developer', 'registered nurse', 'data scientist'). Used in occupation\_analysis, wage\_trends, skills\_demand modes. ## `socCode` (type: `string`): Standard Occupational Classification (SOC) code (e.g., '15-1252' for Software Developers, '29-1141' for Registered Nurses). Overrides occupation name when provided. ## `state` (type: `string`): Two-letter US state abbreviation (e.g., 'CA', 'TX', 'NY'). Used in labor\_market and industry\_workforce modes. ## `industryCode` (type: `string`): 2-6 digit NAICS industry code (e.g., '54' for Professional Services, '62' for Health Care, '52' for Finance). Used in industry\_workforce mode. ## `years` (type: `integer`): Number of years of historical data to retrieve (1-10). Applies to wage\_trends mode. ## Actor input object example ```json { "mode": "occupation_analysis", "years": 5 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("ntriqpro/world-bank-development-goals").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("ntriqpro/world-bank-development-goals").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call ntriqpro/world-bank-development-goals --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ntriqpro/world-bank-development-goals", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "World Bank Development Goals - Free SDG Tracking API", "description": "Free API for UN Sustainable Development Goals (SDG) tracking. No subscription. Track progress by country for poverty, health, education, development metrics. Government data, pay-per-use.", "version": "1.0", "x-build-id": "pcYXP5aMIDQH3fuqd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ntriqpro~world-bank-development-goals/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ntriqpro-world-bank-development-goals", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ntriqpro~world-bank-development-goals/runs": { "post": { "operationId": "runs-sync-ntriqpro-world-bank-development-goals", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ntriqpro~world-bank-development-goals/run-sync": { "post": { "operationId": "run-sync-ntriqpro-world-bank-development-goals", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Analysis Mode", "enum": [ "occupation_analysis", "labor_market", "wage_trends", "industry_workforce", "skills_demand" ], "type": "string", "description": "Select the type of workforce and labor market analysis to perform", "default": "occupation_analysis" }, "occupation": { "title": "Occupation Name", "type": "string", "description": "Occupation name to analyze (e.g., 'software developer', 'registered nurse', 'data scientist'). Used in occupation_analysis, wage_trends, skills_demand modes." }, "socCode": { "title": "SOC Code", "type": "string", "description": "Standard Occupational Classification (SOC) code (e.g., '15-1252' for Software Developers, '29-1141' for Registered Nurses). Overrides occupation name when provided." }, "state": { "title": "State Code", "type": "string", "description": "Two-letter US state abbreviation (e.g., 'CA', 'TX', 'NY'). Used in labor_market and industry_workforce modes." }, "industryCode": { "title": "NAICS Industry Code", "type": "string", "description": "2-6 digit NAICS industry code (e.g., '54' for Professional Services, '62' for Health Care, '52' for Finance). Used in industry_workforce mode." }, "years": { "title": "Years of Historical Data", "minimum": 1, "maximum": 10, "type": "integer", "description": "Number of years of historical data to retrieve (1-10). Applies to wage_trends mode.", "default": 5 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```